1. Field of the Invention
The present invention relates to a noise eliminating device, a noise eliminating method, and a noise eliminating program.
2. Description of the Related Art
In Japanese Patent Application Publication Laid-open No. 5-161191 and Japanese Patent Application Publication Laid-open No. 6-269083, methods using adaptive filters are disclosed. FIG. 7 illustrates a conceptual diagram of an adaptive filter. Generally, an adaptive filter 10 performs a filter operation for an input signal Xn of discrete time n and outputs an output signal Yn. A subtracter 30 to which the output signal Yn has been input outputs an error signal En that represents a difference between a desired signal Dn and the output signal Yn; and the adaptive filter 10 changes the filter characteristics such that the error signal En decreases. Then, by using the changed filter characteristics, the filter operation is performed for an input signal Xn+1 of the next discrete time n+1. Thereafter, the process is repeated.
FIG. 8 is a configuration diagram that illustrates a case where a filter is implemented as a finite impulse response (FIR) filter. This adaptive filter 10 is equipped with a variable filter 11 that performs an FIR filter operation and a filter coefficient generator 12 that updates the coefficients of the variable filter 11 based on an adaptive algorithm. The variable filter 11 is equipped with: a plurality of delay devices 101, 102, . . . , 103 that delay the input signal Xn; multipliers 111, 112, . . . , 113 that respectively multiply the input signal Xn and delay signals Xn−1, Xn−2, . . . , Xn−(m−n), which are acquired by delaying the input signal, by coefficients W0, W1, . . . , Wm−1 that are set by the filter coefficient generator 12; and an adder 120 that adds the outputs of the multipliers and outputs an output signal Yn.
As the adaptive algorithm (the algorithm for adjusting the coefficients of the adaptive filter), a least mean square (LMS) algorithm is frequently used. Alternatively, instead of the LMS algorithm, a recursive least square (RLS) algorithm or the like may be used.
In addition, instead of the FIR filter, there is a case where an infinite impulse response (IIR) filter is used (see, Wu and Others, “Block Implementation of Adaptive IIR Filter”, Proceedings of the Institute of Electronics, Information and Communication Engineers General Conference, 1996, Engineering Sciences, 182, 1996-03-11, or the like). Furthermore, there is also a case where an input signal is transformed into a frequency-domain signal, and an adaptive filter operation is performed in the frequency domain (see Japanese Patent Application Publication (Translation of PCT Application) No. 2006-506929 W or the like).
According to Japanese Patent Publication Laid-open No. 5-161191, a signal that is acquired by delaying a signal received by one microphone is set as a desired signal input of the adaptive filter; a difference signal between the signal received by the microphone and a signal received by another microphone arranged closely thereto is set as an input signal; and an error signal is set as an output signal of a noise canceller. In addition, according to Japanese Patent Publication Laid-open No. 6-269083, a signal acquired by applying a band pass filter (BPF) to a signal received by one microphone is set as a desired signal input; and a signal acquired by applying a BPF to a difference signal is set as an input signal.
In a signal received by the one microphone, a wind noise n0 is mixed in a desired signal s. On the other hand, also in a signal received by the microphone that is arranged to be close thereto, a wind noise n0′ is mixed in a desired signal s′. Here, in a case where the two microphones are arranged to be close to each other, the low-frequency components of the desired signals s and s′ are almost the same.
On the other hand, the wind noises mixed into the two microphones do not have any correlation. Accordingly, as the output of the BPF of a difference signal between the signals of two microphone, n1=(s+n0)−(s′+n0′)=n0−n0′, which represents only the wind noise. The adaptive filter is applied to the output signal n1; and the coefficients of the adaptive filter are updated such that a value acquired by subtracting a resultant signal from the delayed signal s+n0 of the one microphone is minimized. As a result, an expected value E[n0−(n0−n0′)] is minimized, whereby the desired signal s is acquired as the output.
However, practically, even when the adaptive filter is applied to the output signal n1=n0−n0′, it is difficult to acquire an estimated value of the signal n0 with high accuracy. The reason for this is that there is no correlation between n0 and n0′, and the frequency components are distributed to be similar to each other. Accordingly, there is a problem in that the effect of reduction of the wind noise is not sufficient by using the methods disclosed in Japanese Patent Publication Laid-open No. 5-161191 and Japanese Patent Publication Laid-open No. 6-269083.